As I understand it, you don't need 200
temporary variables to do what you
want, as 2 will suffice. Thus your
code, at a hasty hack, seems to boil down
to this. I would still recommend building
up the log likelihood as a sum of logs, not
as a product to be logged later. I don't
understand what you are trying to do,
so can't help further.
set trace off
set more off
cap program drop my_ll
program my_ll
version 8.2
args lnf xb
tempname b sp0
sca `b' = 5
tempvar ed sp
gen double `sp' = 1
gen double `ed' = 1
qui forval i = 1/100 {
replace `ed' = -ln(uniform()) * `b'
replace `sp'= `sp' * (invlogit(`xb' + `ed')) if $ML_y1 == 1
replace `sp'= `sp' * (invlogit(-(`xb' + `ed'))) if $ML_y1 == 0
}
qui replace `lnf' = ln(`sp')
end
Nick
[email protected]
Jun Xu
> Sorry for that mistake. The following is a revised version.
> Still encounter
> difficulty calculating numerical derivatives. I don't think it's data
> problem. I tried to look into mvprob_ll.ado by Dr. Cappellari and Dr.
> Jenkins, and I am stuck there. No one is responsible for
> solving my problem,
> except myself; however, I do need some even slight hint to
> get me through.
>
> ********************************
> set trace off
> set more off
> cap program drop my_ll
> program my_ll
> version 8.2
> args lnf xb
> tempname b sp0
> sca `b' = 5
>
> forval i = 1/100 {
> tempname ed`i' like`j' sp`i'
> gen double `sp`i'' = 0
> }
>
> gen double `sp0' = 1
>
> qui replace `lnf' = 0
> forval i = 1/100 {
> loc j = `i' - 1
> qui gen double `ed`i'' = -ln(uniform())*`b'
> qui replace `sp`i''= `sp`j''*(invlogit(
> `xb'+`ed`i'')) if
> $ML_y1 == 1
> qui replace `sp`i''=
> `sp`j''*(invlogit(-(`xb'+`ed`i''))) if
> $ML_y1 == 0
> }
>
> qui replace `lnf' = ln(`sp100')
> end
>
> use binlfp2.dta, clear
> ml model lf my_ll (lfp = k5 k618 age), technique(nr bhhh dfp bfgs)
> ml search
> ml maximize
>
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